01 Platform Architect Own the shape of the systems everything else stands on.
You will define how a trust platform is built: service boundaries, data architecture, security model, and the standards the whole engineering organisation inherits. Infrastructure portability is a hard constraint — systems that move cleanly between cloud and owned hardware without re-architecture.
You will
- Own end-to-end platform architecture — service boundaries, contracts, data model — as the single accountable technical authority
- Design for portability: containerised services, environment-agnostic configuration, storage that works across S3-compatible and on-premise object stores
- Establish AI-native platform foundations — agentic workflow governance, MCP-compatible interfaces, on-premise LLM serving, vector-database integration as platform primitives
- Embed zero-trust security architecture: mutual TLS, least-privilege identity, segmentation, audit logging as a platform primitive
- Set and enforce engineering standards — architectural review, API contracts, testing, observability — across the team
We look for
- Deep experience owning the architecture of complex multi-service platforms in production
- Strong command of cloud architecture (AWS, GCP, or Azure) and the principles of migrating workloads to owned hardware without re-platforming
- Fluency in event-driven architectures, message queues, distributed data consistency, and failure-domain isolation
- Understanding of platforms where cryptographic guarantees and HSM integration are architectural inputs, not afterthoughts
- Clear technical writing — your design documents settle arguments
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role02 AI Engineer — Semiconductor Intelligence Build the intelligence layer that speaks the language of silicon.
You will build and operate the AI systems at the heart of the platform — retrieval over dense technical corpora, fully self-hosted LLM serving, and the evaluation discipline that makes AI output trustworthy in a domain where wrong answers are expensive.
You will
- Design and build RAG pipelines over semiconductor and regulatory corpora — grounded, citeable, honest about uncertainty
- Operate and optimise the self-hosted LLM inference stack on owned hardware — quantisation, batching, latency and memory budgets
- Build evaluation harnesses that measure usefulness and factual grounding, not vibes
- Engineer guardrails: uncertainty surfacing, output validation, refusal behavior
- Build data pipelines that turn raw technical corpora into indexed, retrievable intelligence
We look for
- Shipped LLM-backed features in production — beyond demos
- Hands-on self-hosted LLM deployment experience (vLLM or equivalent) and vector-database depth
- Strong Python engineering; you treat AI systems as software, with tests
- Retrieval and evaluation depth — chunking, embedding, relevance, regression suites
- Skepticism as a design tool — you assume the model is wrong until shown otherwise
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role03 AI Agent Architect Architect the agentic systems that do real work under real governance.
You will design multi-agent systems that plan, use tools, and execute multi-step work — with the governance layer that makes agents safe on a platform handling sensitive IP: permissions, resource limits, audit trails, and human-in-the-loop gates.
You will
- Architect multi-agent systems using modern frameworks — LangGraph, CrewAI, AutoGen, or equivalent
- Design tool-use interfaces with clear contracts, structured inputs and outputs, and disciplined error handling
- Build agent governance: RBAC, resource budgets, observability, and audit trails appropriate to sensitive-IP work
- Design human-in-the-loop checkpoints where autonomy must yield to judgment
- Define the platform's MCP-compatible service surface so agents are first-class, governed citizens
We look for
- Hands-on experience with modern agent frameworks in production, not just notebooks
- Systems thinking about orchestration: state, retries, idempotency, failure recovery
- Security instinct for agentic systems — capability scoping, prompt-injection awareness, least privilege
- Strong Python engineering and API design
- Judgment about where agents genuinely help and where they should not act
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role04 Data Engineer Build the pipelines that turn design data into dependable intelligence.
You will build the data layer beneath the platform's intelligence — ingestion, quality filtering, deduplication, lineage, and indexing for corpora that range from regulatory documents to design artifacts — portable from cloud to owned hardware without redesign.
You will
- Build ingestion and processing pipelines for technical documents and design artifacts
- Own vector and search indexing — chunking, embedding, refresh cycles, and relevance quality
- Implement data-quality gates, deduplication, and lineage tracking across every pipeline
- Operate data infrastructure across cloud and owned on-premise hardware
- Serve AI and product teams with datasets they can trust — measured, not assumed
We look for
- Production data-pipeline engineering, Python-first
- Hands-on vector-store and search-relevance experience
- Rigor about data quality and lineage — you instrument it
- Comfort with messy real-world documents at scale
- Care for tiering and what should never be indexed
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role05 Full Stack Engineer Build the product, edge to edge.
You will build across the whole surface — Python/FastAPI services on the back, modern React on the front — with the correctness discipline of a platform whose records carry real weight, and deployment habits that keep everything provider-decoupled.
You will
- Build production services in Python/FastAPI — async patterns, dependency injection, typed contracts
- Build product interfaces in modern React — dashboards, verification views, workflow surfaces
- Own features end to end: schema, API, UI, tests, deployment
- Keep services containerised, environment-configured, and provider-decoupled — fast on cloud, portable to owned hardware without rework
- Write the tests that would catch you: negative paths, concurrency, edge cases
We look for
- Strong production experience across backend (Python) and frontend (React or equivalent)
- Database competence — schemas, transactions, query discipline
- API design taste: versioned, documented, boring in the best way
- Performance and accessibility treated as features
- Pride of craft on both sides of the stack
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role06 Cryptographic Engineer Build the proofs at the core of the product.
The product's central promise is cryptographic: tamper-evident records, hardware-anchored signatures, verifiable timestamps. You will implement, test, and harden the signing chains that promise depends on — where correctness is not a quality bar but the product itself.
You will
- Implement and maintain signing services, key hierarchies, and certificate issuance paths
- Integrate hardware security modules and design key ceremonies that survive audit
- Build canonicalization, verification, and tamper-detection logic with exhaustive negative testing
- Work with post-quantum schemes (ML-KEM, ML-DSA, SLH-DSA) alongside classical ECDSA
- Write test batteries that attack our own claims before anyone else can
We look for
- Applied cryptography in production — signing, PKI, HSMs, or equivalent depth
- Standards fluency: FIPS 203/204/205, RFC 3161, X.509, and the discipline to follow them exactly
- The never-roll-your-own instinct, paired with the skill to wire primitives correctly
- Meticulous engineering habits: determinism, canonical encodings, constant-time thinking
- Ability to explain cryptographic guarantees precisely — including their limits
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role07 Quantum Systems Engineer Carry protection past the quantum horizon.
Harvest-now-decrypt-later is not a thought experiment for IP with a thirty-year life. Working alongside the Cryptographic Engineer from day one, you will own the post-quantum posture: hybrid schemes, crypto-agility, and the migration paths that keep guarantees standing as standards move.
You will
- Own the post-quantum roadmap: hybrid classical+PQ signing and encryption in production
- Design crypto-agility into the platform so algorithm transitions are engineering, not surgery
- Model long-horizon threats and translate them into concrete design requirements
- Track and interpret the evolving PQC standards and certification landscape for the team
- Prototype PQ-capable hardware integration paths ahead of production need
We look for
- Strong modern-cryptography grounding with genuine post-quantum depth
- Understanding of lattice-based schemes and their engineering trade-offs
- Systems skill — you ship working code, not only analyses
- Judgment to separate durable standards from noise
- Writing that makes hard trade-offs legible to non-cryptographers
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role08 Security Engineer Defend infrastructure worthy of the IP it holds.
Customers will hand us the most valuable artifacts they own. You will build and run the defenses that make that rational: hardened perimeters, zero-trust networking, detection and response, and the operational compliance obligations of Indian infrastructure.
You will
- Own cloud security architecture: segmentation, egress control, secrets, identity
- Harden services and deployment paths; drive findings from audit to closure
- Build detection, alerting, and incident-response runbooks — including regulatory reporting clocks
- Prepare and pass external assessments (VAPT and equivalent) as routine, not events
- Threat-model new features before they ship, with authority to say not yet
We look for
- Production security engineering across cloud and Linux estates
- Hands-on Kubernetes, network policy, and secrets-management depth
- Familiarity with Indian regulatory obligations — incident reporting, log retention — or the rigor to master them fast
- Attacker's imagination, defender's discipline
- Calm, written, blameless incident practice
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role09 EDA Design Engineer Run real design flows — and make them reproducible.
You will bring production chip-design flow experience into the platform: synthesis, timing, and physical implementation, executed through toolchains the industry actually uses — and engineered so every run is deterministic, metered, and fully accounted.
You will
- Build and operate design flows — synthesis, STA, floorplanning through routing — as reliable platform services
- Work across industry-standard tools (Cadence, Synopsys, Siemens flows) and open-source toolchains (OpenROAD, OpenLane, and peers)
- Engineer containerised, deterministic tool execution with complete artifact capture
- Design job scheduling and resource management for long-running compute
- Make reproducibility a property of the system, not an aspiration
We look for
- Real production experience closing timing on actual designs
- Deep RTL fluency (Verilog/VHDL) and full physical-design-flow understanding
- Strong Linux, containers, and build-system depth
- Respect for the licensing and compliance realities of commercial tools
- Patience for the unglamorous engineering that makes flows actually reliable
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role10 Silicon IP Design Engineer Design reusable IP the industry can trust.
You will design and verify reusable IP blocks and processor cores — from architecture through verified, packaged, integration-ready delivery — and help define what disciplined, provenance-tracked IP development looks like on the platform.
You will
- Design, develop, and verify reusable IP blocks and processor cores, owning the full lifecycle to signed-off delivery
- Build and maintain IP libraries with rigorous version control, documentation, and independent verification
- Define clean interfaces and packaging standards that make IP genuinely reusable
- Exercise the platform's provenance and custody workflows on real design artifacts
- Partner with domain and tooling engineers on format handling from RTL to GDSII
We look for
- Proven IP or processor-core design experience through verification sign-off
- Strong RTL discipline — clean, synthesisable, well-structured code
- Verification depth: testbenches, coverage, assertion-based methods
- Documentation habits worthy of third-party integration
- Interest in what makes IP provable, not just functional
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role11 Semiconductor Domain Expert Be the domain conscience inside the product.
Our users design silicon. The platform must speak their language natively — formats, flows, constraints, and the unwritten realities of tapeout. You will encode that reality into the product and be the credible technical authority in the room with design teams.
You will
- Encode design-flow knowledge into product behavior: formats, checks, terminology, workflows
- Define how design artifacts — RTL through layout — are represented, validated, and protected
- Review AI outputs and platform features for domain correctness and credibility
- Be the customer-facing technical authority in deep evaluations
- Shape roadmap priorities from real design-team pain
We look for
- Years inside real chip design: RTL, verification, physical design, or design management
- Fluency across the format landscape from RTL to GDSII and the flows between
- Ability to translate practitioner reality into product requirements
- Credibility with senior design engineers
- Curiosity for what software and AI can genuinely change in this field
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role12 Technical Recruiter Find the people who will set the standard with us.
The first fifteen hires define the company. You will own that pipeline end to end — sourcing exceptional engineers across semiconductor, AI, and cryptography, designing assessments that measure what matters, and giving every candidate an experience worthy of the brand.
You will
- Own full-cycle recruiting for deeply technical roles, sourcing through close
- Build research-grade networks in niches where the best people are not looking
- Design interview processes that test fundamentals, judgment, and AI-collaboration skill
- Run the pipeline with data: conversion, velocity, honest signal quality
- Partner with the founder on offers, levels, and closing
We look for
- Technical recruiting experience for roles you genuinely understand — semiconductor, AI, security, or deep tech
- Sourcing craft beyond job boards
- Structured hiring-process design; assessments that predict, not perform
- Compensation benchmarking capability for deep-tech roles
- AI-native working style — you use AI to accelerate sourcing, research, and documentation
Level: set by demonstrated ability, not years. Exceptional earlier-career candidates are read with full attention. AI tools are part of our interviews — bring your AI favorites; we would love to see how you think alongside them.
Apply for this role